Where is your POSEIDON now?

A minute of POSEIDON

• POSEIDON is an agent-based model
  • Scalable
  • Modular
• POSEIDON has a few use cases:
  • Scenario evalutation
  • Optimization
  • Reiforcement Learning

Work in progress

• Calibrating and validating West-Coast DTS model
• Develop the infrastructure for Indonesia
• Data degradation for West-Coast fixed gear model

Calibration

• We have two target data-sets:
  • Landings/quota attainments
  • Logbook data
• Calibrate in two steps
  1. Fix agents statistically
  2. Find catchabilities that generate correct quotas
  3. Fix catchabilities but let agents act adaptively
  4. Find behavioural parameters that replicate logbook

Calibration - Results

Calibration - Results 2

• Looks realistic with simple adaptive agents
• Adaptive agents are very risk-averse:
  • Calibrated exploration rate is 3.5%
• It’s trivial to find more performing agents:
  1. Are we picking up an approximation error from the way we distribute fish compared to the real world?
  2. Are fishers just not that profit maximizing?

Calibration - 15% exploration rate

Indonesia

Fixed Gear Allocation